Intro by Host

Nirupama: Hi, you are now tuned into Coefficient, a podcast brought to you by TheMathCompany. I’m Nirupama, a journalist, researcher, and podcaster, currently the content lead for thought leadership and podcasts at TheMathCompany. In every episode of Coefficient, we talk to experts and deep dive into compelling topics related to the present and future of data analytics and AI for business intelligence.

This is episode three, and today we’re talking to two experts at TheMathCompany, Dmitry Pavlov and Prabal Majumdar, about the opportunities and challenges in the retail media marketing space. I’ll just take a moment to give a quick introduction about our guests.
Dmitry is the Head of Retail Media Analytics Practice at TheMathCompany. He has several years of experience in the tech space and also in R& D, where he worked with companies including Yahoo, Yandex, Criteo, and Walmart e commerce. He played a leading role in building Walmart Connect, which is Walmart’s retail media arm, and growing it to several billion dollars of ad revenue.
Prabal is the principle of customer success at TheMathCompany. He’s an analytics leader with nearly 17 years of experience in predictive modeling to influence data-driven decision making, not only for retail media, but also other business solutions. He has worked and led high performing data science teams at Amazon, Hulu, and Walmart Connect, among others.
I’m really excited to talk to them today.

Episode Conversation

Welcome, Dmitry, and welcome, Prabal. It’s so nice to have you here on the third episode of Coefficient, MathGo’s podcast. So, I first wanted to get started with a question that sets the context. So retail media networks are gaining a lot of strength.

Back in 2012, Amazon made $600 million on retail media and it was a sort of a pioneer in the space. 10 years later, now there are 600 retail media networks and they claim a total advertiser spend of about $40 billion. And there is a projection that by 2027, retail media will account for 60% of overall digital spending, right? And it will grow to $160 billion or more in the U. S. alone. So, I want to start with asking you what is the big deal about retail media marketing? What is in it for retailers? And what is there for brands?

Dmitry: So, I think, Nirupama, the biggest thing, at least from my perspective, is that this is an interesting case where brands can actually get, closed loop targeting, measurement, reporting, and optimization—which, previously, they were not able to get.
And so I think when Amazon first appeared on stage, everybody thought that since big retailers were haggling a lot with brands on the pricing for for goods, there is no money in the system. And so, Amazon—as I think in many cases they did in the past—they proved to us that this is not necessarily true, and that the brands still have deep pockets of money, to spend on marketing.
And so retail media in general, they think as this is a marketing for the brand by a retailer, near the point of sales. Though I think these days, the notion of retail media is much wider. But the point there is that the brand very typically doesn’t have access to customer consumer purchase data, to consumer behavior, at the point of sales, or in general, as the retailer.

And this is what makes the advertising with retailers such a lucrative deal for the brands. Now, the due diligence, on the retailer—or retail media network that they run—is that they really need to enable these four pieces, right? Which is closed loop targeting, measurement, reporting, and optimization.
And so, you know, what makes for a successful retail media network is that they enable these pieces, and are able to prove to the brands that they, in fact, are driving purchases—incremental purchases in a lot of cases—which is important. And the brand is willing to pay a lot of money.

And it’s almost like we need to feel for the brands, right? Because they are in a somewhat unempowered position, you know, they don’t own the point of sales, right? And so retailers who are able to come to the brands whose products that they’re carrying and basically say: look, we can actually enable insights, analytics and closed loop targeting and measurement—they are the ones who are able to reap the benefits, and make extra money.
And for the brands, obviously, you know, there is this other side of equation, which is: Finally, we’re able to get a good handle on targeting, reporting, and optimization. And of course, we have other strategies, right? So we can go and still hit Google, Facebook…I think it’s an interesting question of how advertising between like big channels like this is going to pan out over time. And we can talk about this, I guess later, but the point there is that the brands finally got this great channel where it all finally can make sense, from measurability and optimization perspective, and I think this is an awesome value proposition.

Prabal: Yeah, for me, how I’ve been seeing retail media is like: retail media addresses three very, very big cornerstone issues. It takes away this “spray and pray” aspect of marketing, right?
Before retail media was there, brands used to, you know, “spray and pray”, like they would throw a lot of random ads and pray a human saw it and acted on it, right? So it was like living on a prayer, if you want to quote Bon Jovi, right? They were living on a prayer in many ways, with their media investments. That’s one piece…

Dmitry: Facebook, by the way, is an excellent place for that.

Prabal: Yeah, yeah, exactly.

Dmitry: A lot of cheap advertising to go around. Just like throw it there. Sorry, Prabal.

Prabal: Yeah, absolutely. And the other aspect…you know, before retail media came and the closed loop measurement and attribution came into play, there was also this factor of “Trust me” marketing, right? I mean, as brands… whoever I’m investing with would say like: “Hey, trust me, the marketing works.” That’s completely out of the equation now. The retailers are like held accountable… like they let’s say I’m investing with retailers A, B and C. A, B and C has to show performance in their own way and say like: Hey, Dmitry saw my ad and acted on it, or Nirupama saw my ad and acted on it. So that’s the big part of it.

The other thing is…what I am very, very amazed, as a true believer in democracy, that with retail media, the rise of retail media, the duopoly of Google and Facebook is getting broken, right? So if you think about 10 years back, right? I mean, there were only like two very big players in advertising, like 95% of all media dollars would flow through either Google or Facebook at one point. That’s getting fragmented now, right? I mean, the big chunk of dollars are flowing through Amazon, the Walmarts of the world, and the retailers of the world.
And rightfully so—because they own the first party data. And if we believe data is the new oil, then they are actually now capitalizing on their oil, right? They’re waking up, and I’m really happy with how retail media is evolving and how all the retailers who are sitting on massive oil reserves, they’re now mining their oil and making money out of it, rightfully so.

Nirupama: Okay. Thank you so much for giving us that context. So I’ll jump straight into the main question that I have for both of you. So today there are multiple retail media networks of varying successes and varying levels of revenue that they’re generating. And I understand that there’s a lot of money-making opportunity for retailers that currently remains untapped. Similarly, there also might be several challenges that brands face with making use of these retail media networks, right? So how can data and analytics help solve these issues?

Dmitry: So I think Nirupama, this is a great question. And I will just second what Prabal just mentioned, which is: the first party data that retail media networks have in their possession—what he mentioned to be oil reserve—I think is an essential part. And so, if you are a retailer, you’ll need to be collecting the first party data, because especially in this day and age where we’re talking about privacy and it takes, if not the central stage, but it really affects advertising.
Having a relationship with your customer who shops with you—if you are a retailer—is essential because it really allows you to collect data from any interaction that a customer is doing with you. And then subsequent to that, you can actually leverage this data for a lot of things. You know, to personalize on your own website for your own marketing and for retail media, which is enabling the brands to access the customer. So I think first party data is really essential for performance. And so if you are a brand, you’re actually really looking for this enablement beyond performance, right? Because performance is the ultimate goal, right?

You know, I need sales. And so, under the banners of like brand advertising and awareness and whatnot, I think, what’s hiding, right? Like if you kind of unpack the onion: brands really want sales. And I think this is where the goals of brands and retailers, they actually coincide. Everybody wants sales; it’s just a question of how to get there.
And the interesting part to me, which I really want to also emphasize for our listeners is that I think the brand really needs to get more empowerment in terms of data and analytics as to where exactly they need to go and mine to get the gold, right? Like, to get to those customers who are going to buy and react to their existing or new products. And the reason why this is essential is because the brand doesn’t have any of the data that the retail media network or the retailer has, and it is incumbent upon the retailer to actually enable the brands to have a wide reach to the right customers.
And I’ll give you maybe a couple of examples just to kind of make it very concrete. So for example, I am currently on Walmart, right? And I’m using a set of keywords to target my customers. I really need and want an expanded set of keywords that would actually drive—if not better—at least similar performance.

And so the question is, how do you do this? If I am targeting a certain audience, and I know this audience is doing well for my targeting, is it possible for me for me to get more like this? So, you know, some kind of look alike modeling. And so what you will see as a common topic going forward is that brands really want to get access to better insights and analytics that are data-driven from the retailer. And there is a variety of ways it is happening today in this world, right? Like, either through clean rooms on the one hand or through platforms like Walmart Luminate. We at TheMathCompany is driving a lot of solutions; some of them are AI based, some of them are just data-driven for retailers where we are extracting, from retailers, data—things that would be extremely simple; such as, for example, people in, I don’t know, Midwest, are buying detergent on the first Wednesday of every month, more so than on any other day.
You can imagine that if you are a brand selling detergent, this is actually a very interesting piece of information that you can use for marketing, but that is, completely obfuscated and unavailable to you if you are not sitting on the wealth of retail data. And retailers actually have a lot of insights like this to offer, which brands can later leverage for their marketing.

Prabal: Yeah. Just to add to that…my take on this, right? We spoke about data being the oil and the retailers sitting on massive amounts of oil, right? I mean, if we stretch that analogy a little more, right? I mean, let’s say I tell you: Hey, you have like 10 billion dollars worth of oil in your backyard, but hey, you have a shovel to dig it up. It’s not going to end very well for you. So to monetize that 10 billion sitting in your backyard, you will need the right kind of equipment, right? So you need those big drills, those big rigs that you associate with the oil industry. So I think data and analytics, and in, extension TheMathCompany, where we bring those big rigs and we help you dig up that oil so that you can monetize what’s sitting right underneath your feet.
If you have shovels, it’s not going to end very well. Let’s put it that way, right? It’s gonna take like hundreds of years for you to reach that oil. So data analytics, it goes without saying it’s very, very imperative. I cannot stress enough why data analytics and, if I could add something, it would be the infrastructure—you need to really invest a little bit on your infrastructure and it gets you outsized returns, right?

So just to give you an example, right? Let’s say, take your, your typical, like, let’s say you go to a store, you transact, you buy your grocery and come back, you get a receipt, right? The receipt itself means…doesn’t mean much, but the moment I start stringing together those receipts like over a period of time: let’s say, two years worth of your purchase receipts. If I could like string them up in a temporal manner, like in a, over a timeline, right? It tells a lot about you, Nirupama or Dmitry for that matter. And I can say how are you worried about inflation? How are you worried about the economy, all those.
You have left those breadcrumbs, of your purchase behavior. And brands absolutely want that. That’s the goldmine of data, right? How much are you cutting down on your food expenses or how much are you cutting down on your discretionary spending? I mean, all the answers lies in those breadcrumbs of your receipts.

Once they’re strung together, it’s strung around your identity graph. I mean, it tells a complete picture of what do you care about? What are your preferences? What do you want to buy next? Everything can be done from there. So that’s the goldmine of information that retailers have, and they are sitting on. And data analytics—and if I could add infrastructure, right? I mean, with the right infrastructure, this can be mined and it can be monetized and it helps the brands, right? I mean, why I love the promise of retail media is closed loop attribution and making media way more addressable and relevant.
They’re not wasting impressions, right? I mean, let’s say they’re not like, if this information, like all this information is correctly syndicated through retailers, right? I mean, we are not showing like diaper ads to people who do not have infants or children in their household.

So, the problem of wasted impressions and wasted media spend—it’s kind of taken out of the equation. Like, you don’t want to show me ads of dog food, because I do not plan to have a dog in the next 10 to 20 years at least, unless something changes drastically. So it’s a wasted impression. So I think that’s where to kind of bring home that point, right? I mean, it makes data, analytics, and if you want to stretch it—machine learning and AI—makes it way more relevant for the right impressions to reach the right person and so that the right customer takes the right action in terms of purchase and transaction. That’s what the brands want.

Dmitry: Just maybe one thing to mention. Uh, this is all first party data, right? That Prabal was mentioning. So in other words, you know, the era of data where customers are just browsing, right? Like I’m doing something anonymously. You know, this is kind of like that single receipt that Prabal was mentioning that is—if unattached, right? Like to the rest of the history of this customer is, uh, largely useless.

And so, um, we really want to kind of drive this point with a lot of our clients. That first party data is really essential, right? And so if you did not start strategizing around this and having the right infrastructure yesterday, then time is actually today and that will pay off tomorrow.

Nirupama: Yeah. This is really interesting. When we were discussing about this earlier, you had mentioned Retail media is essentially, I mean, it’s not really a piece of media, but it’s just data in a wrapper. I really found that interesting.
So I want to follow this up with my next question, which is, just zooming out a little bit, is retail media network—you know, setting up a retail media network—is it for every retailer? Or should retailers be of a certain size or of a certain type? Let’s say, you know, a grocery retailer is better suited for having a retail media network…to be able to succeed in retail media marketing.

Prabal: My take on this is, I have a slightly biased view towards the grocery retailers. Like, typically what I believe, like in my heart of hearts, is that the grocery retailers—like, right off the bat—have a outsized advantage in winning in the retail media space.
It’s the sheer…the habitual aspect of it; the high frequency, right? I mean, I need to buy my grocery every 15 days, right? I do not buy a TV every 15 days. I buy my TV every three or four years. That being said, we still love the non grocery retailers as well. They have a different value proposition. We’ll come to that.
But the grocery retailers in general, like even with a very small amount of traffic, I mean, you can think of a very small amount of customer base, they can generate a tremendous amount of traffic, right? I mean, provided they get their app personalization engine and stuff going very well. Like let’s say you are a small retailer based out of somewhere in California, but you have a very loyal fan base. I mean we have seen many such grocers out here, even in Canada, where I am. Like, there’s a massive fan base and very high net worth individuals who shop in those retailers. But it’s a relative, like it’s about top 1 or 2% of the population. But it’s that massive loyalty that they are cashing on. And the best part about grocery retailers is they have all this little loyalty programs, right? I mean, you scan your little, like fob in your key and all the, and whatnot, and if you get your app game going really well. You get those highly personalized coupons based on your, like what wine you bought or what type of artisanal bread you eat and all this kind of stuff, right?

They can really monetize things much faster and much easier. Like they have an outsized advantage, right? Off the bat.
That being said, the non grocery retailers, no need to feel disappointed. No need to have a broken heart. You can still win, because you are selling big ticket items, right? I mean, no one is going to your store to buy a 5 dollar loaf of bread. People are going to buy TVs and all that. So you need to focus on the other aspect of retail media, which is figuring out the journey-based analytics, the journey based measurement, right? I mean, where your ads and impressions are able to move me in the right direction to purchase like my 3,000 dollar TV.

If you can kind of nail that piece out, I mean, that’s a very solid information that any TV manufacturer would want to…and they see like, consistently you can move the needle on that, they would keep investing with you for sure. So these are like two different types of game. So one is like playing basketball, the other one is playing soccer. So it’s just two different games with two different set of rules. Yeah.

Dmitry: I think what was interesting….I got just maybe kind of one click on this because I love this train of thought.
You know, there is no one size fits all solution, right? So for grocery retailers versus non grocery retailers, potentially insights analytics, right? What you’re doing is different. And so, grocery retailers, I think, they have an advantage, definitely. Because there is a lot of repeat shopping.

The disadvantage there is that if they’re trying to prove that the ads are bringing incremental revenue, right? Like as in I show an ad, and then this ad is actually influential to bring in either more customers, or bigger basket sizes. That actually may be problematic here because, you know, if I am a creature of habit, and I put everything in the basket—you know, pretty much the same stuff all the time, is there incrementality? And so in fact, the personalization solutions that some of the retailers are working on—and I know this firsthand—is just like, let’s create the basket for the customers, right? Because this enables them to check out much faster, and improves the customer satisfaction and whatnot. But guess what, the flip side of it is that, if I’m almost not touching the basket and check it out real fast, then it may be a problem that there is not much of incrementality.
And I think a lot of brands, especially like top brands these days, they really want incrementality. And then, you know, what Prabal was talking about in the non grocery world: it’s almost like there is no question about incrementality, right? Like if you’re buying your TV once in five years, right? And you actually drove this particular purchase. I mean, very good chance that it is incremental. And so, the brand is not really even necessarily looking for the proof of incrementality, but what they want is to understand how that journey resulted in a purchase. And kind of by analogy, how they can access the customer at every particular point of consideration so that they can influence this decision properly.

And so I think it’s incumbent still upon the retailers to understand very well ,how their customers are shopping with them, and to provide these insights to the brands. And these are going to be essential, like really key golden nuggets of information that the brand can leverage for marketing.

Nirupama: Yeah, this is really helpful to understand how different types of retailers could be thinking about retail media network. So leading from that…we sort of touched upon this before, but I just wanted to check if you have a few more points to add on your advice for retailers who are just venturing or who are contemplating about venturing into the whole retail media space and wanting to set up their retail media network.

Dmitry: My sense is that there are really low hanging fruit where pretty much any retailer can start and make money early on just to prove out the point that there is more money in the system. And the idea there is very simple. Brands really love to get an understanding of how their customers shop, why their customers choose them and not their competition.
And to the extent that the retailer has data that can prove that, they are in the game. This is where the money can be made, without necessarily serving any ads, or measuring performance. I think this can come at the later stage. But just to be sure that, you know, I’m coming to my C suite people and I’m actually telling them: look, we have an opportunity. And, I think…maybe I’ll just say this: in a lot of cases, the way retailers are thinking is that they’re looking at Amazon and Walmart, and Instacart, and like top retail media networks and they’re like, well, we really want to be there, but you know, the whole task of setting things up seems audacious.
And I think in a way, it is it is a journey, right? And so if you look at Amazon or Walmart, it took these big retailers years to get to where they are and this is through investment; through a lot of work that they actually were able to prove to the brands that they’re worth the money that are being invested with them.

And so I think this is going to be a journey, for every retailer that chooses to do a retail media network now, for them to be successful. It is the data that is essential. And so, you know, if the data is an essential piece, the first party data that they collect from their customers, then this is exactly where they can start.

And, you know, it doesn’t necessarily have to be media serving, because media serving is heavy, right? Like you need to enable all of these pieces in the closed loop that we were talking about, which is, you know, targeting, measurement, reporting, and optimization. So I would, I would actually do that, but do it maybe as a second step, when the whole kind of concept is proven in the context of a given retailer. And what I would do if I’m contemplating things is, I’ll just take the data and think about how I would wrap it in a way that the brands that I’m working with, or the suppliers that I’m working with, will find it enticing and useful to leverage for marketing. And if I’m able to do this, then the game is on.

Prabal: That being said, I really believe it depends on…yes, you need to have that critical mass; you need to have a little bit of traffic and all that, and we can assess that, right? You need to be pragmatic. I mean, if you set out with goals, like, okay, in year one I will make revenues like Amazon is doing, that’s a fool’s errand, if you will, right? I mean, you will never get that in year one. It’s a long journey. You need to plan…like you need to set your targets in the right way, like as a function of your traffic. Like, okay, I have this much of traffic, my traffic is whatever—like one-tenth of Amazon—you can still monetize a big chunk of it, and you can still make a good amount of money. I mean, it’s non trivial amount of money.

The best part right now is we are past that wild west phase of retail media. Now, there are a lot of solutions. There are like out-of-the-box solutions that can help start helping you run a retail media network, with very minimal set up cost. But yes, the infrastructure, the back end piping and plumbing that still needs to be done. And that’s where, like, MathCo comes and folks like Dmitry and me, we advise and we can actually help you, soup to nuts, to get those things done. So, yeah, reach out to us and we will be happy to advise you and, you know, walk the whole 9 yards with you on your retail media journey.

Dmitry: It’s kind of interesting. I think, Prabal, your point that you’re making, right? Which is, it’s not necessarily about small retailers who are kind of like, nah, you know, should I do retail media? Should I not do retail media? It’s even like the largest ones out there, you know, who seem to not be doing retail media. And it’s almost unclear why not, right? You and I had this discussion offline, right? And, you know, I think it’s still puzzling.

But I think, you know, the flip side of it is: retailers would always think about how their margins are shrinking, and the economy is bad, and how the customers, like, you know, are flowing…So the point there is that, you run retail media, one way or another, through insights, analytics, you know, you serve it, or you measure it, whichever way you do it, right? As long as you’re bringing the value to your brands and suppliers, you are actually getting paid full, hard cash. That actually is just pure profit, most of it, right? Unless you do off site. Like, if you are basically serving your own ads on site, right? Or you are selling insights and analytics off of your data yourself, it is pure profit, right? And so this is what basically becomes an increase and improvement to your margin.
And I think it was very interesting because, you know, in case of several retailers, we had this discussion whereby, I think the understanding that should be there—which is not necessarily, I guess, there—is that you can always, as a retailer, run your own marketing. You still need to have a lot of things that we were talking about in this call, which is data and the right customer graph, you need to basically collect all of the receipts and the first party data, is playing an essential role.
But then, even though you’re running your own marketing, you can actually not pay for that marketing yourself, right? You can actually allow your brand to come in and pay for it or to subsidize it. Why? Because they’re as interested as you are to drive those sales. So as long as you’re able to prove to your brands that you’re actually bringing value, they will come in and participate with you in this equation.

And so I think this is an essential part. It’s basically like, if you are a retailer, think about doing marketing on your data with your customer base, but paid for by your brands. And the reason why they would do this, is because you are driving a lot of value to them, provably, right? And so I think this is, this is like the—if you will—holy grail of retail media. Like where you’re not only getting to make those sales as a retailer, but you’re also not paying to enable that, you know, you’re leveraging your data and do it through your brand.

Nirupama: I just have a couple more questions. So both of you, you have worked in the space for a really long time, and you sort of know it in and out. So I’m curious to know: what are the most innovative retail media solutions that you have seen recently?

Prabal: So I think one of the most innovative retail media solutions that I’ve seen is creation of audience at scale. Like I’ve seen in some instances, using NLP models and all that, like you are just typing “I want to create an audience of people who bought dog food and also are health conscious.” I’m oversimplifying it. So you’re typing a few very simple parameters and your audience is created right in front of you – the audience, the power, the size of the audience. A lot of estimations are run on top of it and all that. And this whole workflow takes a few hours. They’re like, “Hey, I want to reach out to the Dimas of the world.” Because I see Dima in front of me.

So I’m just saying, that can be done. Like five years back, it would take like weeks if not months, but now it’s like a matter of hours. So it’s literally like saying something like: “Hey, I mean give me all the people who have purchased a purple shirt and who also run marathons, right? That’s an easy definition of Dima, right? So it can be inferred from your purchase data—from those receipts, right? So that’s something I’ve seen, like, getting done at scale, insights to audience. And that makes me… you know, in my previous places I’ve worked in, we have done it at scale and I feel very… I mean, it’s like how this thing can be enabled in this fast, low-latency computing environment, in the world of low-latency computing that we live in today, right? I mean, it can be done so fast and these audiences can be activated. That’s a real innovation that’s kind of playing out.

Dmitry: Yeah, I want to maybe mention just to add to this, the advances of AI.
It actually, you know, is really funny to me because, you know, everybody thinks that AI just came. I think, you know, AI came like 20 years back. Like, for as long as I remember myself, AI was there. And so in fact, a lot of models that we built in the companies that I was previously with, be it Yahoo or Criteo, or Yandex, you know, they were actually data-driven.
They were accounting for feature interactions, and they were modeling customers in the context of certain activity and certain kind of space that they were in, and we were making better predictions with better models, right? And this is what artificial intelligence is all about, right?

Like, it’s basically clever statistical analysis of the data, right? Extracting the right information for the purposes of enablement of relevance, right? Like in the given context. So I think, you know, I has become really very life changing, I guess, on the one hand, but on the other, like, very clearly in front of everybody these days, right?
Like, we all kind of know large language models. And so I think AI playing a really key role in what is happening with relevance and enablement of insights and analytics; to a point where you can take an individual customer, right? Like either me or Prabal, or you

Nirupama, right? And, you know, if there is first party data that retailer has against any one of us, then that retailer over time can be significantly more relevant, in real time.
And as you can see, this is no longer “spray painting” that Prabal was mentioning that was happening on Facebook, or probably still is happening on Facebook. It is no longer even audiences of people who have certain characteristics—like marathon runners.
I mean, this is an improvement, obviously, over spray painting, but then if you take this to a limit, you can take an individual customer—one guy, or gal, and you can be relevant to them in a moment. Like in this particular instance, right?
And if something changes in their behavior, like they, for instance, just checked out the basket. This information, if you have this first party data enabled and infrastructure enabled, it basically flows in and all of a sudden the relevance, of certain items falls, the relevance of certain other items goes up. And you can now recommend different set of items in the context of what you know in the moment.

And so I think this is absolutely an exciting time where we can be really understanding our customers to an individual level and be relevant for them. And I think again, the enablement piece for that is data and then artificial intelligence, right? Like, which, you know, is basically kind of building large scale models one way or another off of this data will enable a lot of things, right? Like, relevance obviously is one, but then there is more—understanding language, extracting insights and analytics automatically. Some of these solutions, we actually have in toolbox, that are ready to go and deploy for the customers.

Prabal: Just to add to that, right? I mean, “Hey spray and pray advertisers, please stop showing me diaper ads.”
“I mean, not going to have a kid anytime soon. I paid my dues. I paid all my money to you when my children were growing up. Now they’re much bigger. So please, please don’t show me diaper ads.”

Dmitry: Please, please.

Nirupama: Thank you so much for taking the time, Dmitry and Prabal for talking to me today. It was a great conversation!

Dmitry: It’s a pleasure. Thank you. Thank you so much for having us.

Prabal: Thank you.

Outro by Host

Nirupama: Thank you for tuning into Coefficient. Hope you found this conversation insightful. I certainly did. If you want to know a little bit more about retail media marketing and about how to set up your own retail media network, then you should check out TheMathCompany’s retail media site. I will add the link in the description. In upcoming episodes, we will be discussing generative AI in the business context, effective revenue growth management strategies, among other things. Do subscribe to the show on Apple podcasts, Spotify, or YouTube—wherever you get your podcasts—to be alerted every time a new episode is released.

Goodbye, and have a nice day.